IBM Quantum Hub at the
University of Melbourne
The IBM Quantum Hub at the University of Melbourne offers a complete approach for Members to gain early entry into quantum computing with the support of deep research expertise and the global quantum community.
A new way of thinking
Quantum computing is moving rapidly from proof-of-concept to practical applications in science and business. Developing at a breathtaking pace, we are witnessing a period of evolving interaction between researchers and application developers.
Harnessing the creativity to drive commercial applications will depend on new thinking and new software, developed in parallel with the advancing power and reliability of quantum computing hardware. Early-adopters who drive the development of quantum software in their field will benefit from a strong IP position that will be hard for fast-followers to challenge or replicate.
Australia's only University-based IBM Quantum Hub
Led by Professor Lloyd Hollenberg in collaboration with IBM, the University of Melbourne is the sole university-based IBM Quantum Hub in Australia and New Zealand. The team has worked in quantum computing for some two decades – during this time they have created the blueprint for a full-scale silicon quantum computer and recently set a world record for quantum entanglement on IBM Quantum devices. Through the Quantum Hub, the team is at the forefront of research into practical quantum computing.
In 2018, the team launched the web-based Quantum User Interface (QUI) – a quantum computer simulation environment for software development and training the new generation of quantum programmers.
Quantum computer technology will evolve rapidly, with members of the Quantum Hub at Melbourne positioned to direct that future, working on IBM’s most powerful quantum computers to develop software and expertise for the benefit of their sector and broader society. Professor Lloyd Hollenberg
IBM Quantum is advanced quantum cloud technology – several real quantum computer devices and simulators available for use through the cloud – enabling Fortune 500 companies, startups, national research labs and academic institutions to run experiments and explore use cases.
These devices are part of the IBM Quantum roadmap, an initiative to build universal quantum computers for business and science. You can stay up to date with IBM Quantum developments at the IBM Quantum blog.
Foundations of quantum technology
Quantum bits or qubits are quantum mechanical systems, like the state of a single atom or even a microscopic superconducting circuit. Classical computing works with bits, and a bit can only ever be 0 or 1. Qubits can be effectively both 0 and 1 at the same time.
This quality of qubits, called quantum superposition, together with the related phenomenon of entanglement, is where the remarkable increase in computing power begins.
As the number of qubits grow, superposition allows the quantum computer to represent exponentially increasing sets of numbers. To get a sense of what this means, imagine putting one grain of rice on the first square of a chessboard. Now double that number on each square and by the end of the board you’ll have 92 billion tonnes of rice.
Carefully choreographed sequences of quantum logic gates – the quantum software program – manipulate superposition and entanglement across the vast array of quantum information, to expand computational power.
How does IBM Quantum help research and development?
There are problems that today’s computer systems will never be able to solve, such as accurately simulating large interacting systems, or solving certain optimisation and machine learning challenges. These kinds of problems get exponentially harder as complexity grows even a little, and for problems above a certain size classical computer systems simply run out of steam.
However, quantum computers working alongside classical computers may provide solutions. See the potential near-term applications for quantum computing.
Like the early stages of the digital revolution when no one could imagine how finance or logistics – or the very rhythms of daily life, would be transformed – we can’t yet predict where quantum computing will bring the greatest advantages.
Potential near-term applications for quantum computing
The first business use cases for quantum computing have yet to be determined. They may include, but are not limited to:
- Pharma and Materials, untangling complex molecular and chemical interactions to discover new drugs and materials
- Supply Chain and Logistics, finding solutions for more efficient logistics and global supply chains
- Financial Services, finding new ways to model financial data and isolate risk factors to make better investments
- Artificial Intelligence, enhancing machine learning, hybrid quantum approaches to data classification.
At the Quantum Hub, staff and students are engaged in a range of research projects, spanning fundamentals of quantum information and quantum physics of IBM devices, through to applications in a number of areas.
Research themes
Applications of quantum computing: traffic optimisation and routing, machine learning, materials, chemistry, finance, bioinformatics and cybersecurity.
Science of quantum computing: large-scale entanglement, logic gate characterisation and improvement, HPC benchmarking, and quantum error mitigation.
Recent Quantum Hub papers
"Direct observation of dynamical quasi-condensation on a quantum computer"
Phillipp Frey, Stephan Rachel
https://arxiv.org/abs/2411.02510 (Nov 2024)
"Quantum Hamiltonian Embedding of Images for Data Reuploading Classifiers"
Peiyong Wang, Casey R Myers, Lloyd C L Hollenberg, Udaya Parampalli
https://arxiv.org/abs/2407.14055 (Jul 2024)
"Teleporting two-qubit entanglement across 19 qubits on a superconducting quantum computer"
Haiyue Kang, John F Kam, Gary J Mooney, Lloyd C L Hollenberg
https://arxiv.org/abs/2407.02858 (Jul 2024)
"A Fast and Adaptable Algorithm for Optimal Multi-Qubit Pathfinding in Quantum Circuit Compilation"
Gary J Mooney
https://arxiv.org/abs/2405.18785 (May 2024)
"Adversarial Robustness Guarantees for Quantum Classifiers"
Neil Dowling, Maxwell T West, Angus Southwell, Azar C Nakhl, Martin Sevior, Muhammad Usman, Kavan Modi
https://arxiv.org/abs/2405.10360 (May 2024)
"Calibrating the role of entanglement in variational quantum circuits"
Azar C Nakhl, Thomas Quella, Muhammad Usman
Physical Review A (2024)
“Mechanisms of ergodicity breaking - from time crystals to Hilbert space fragmentation”
Philipp Frey
PhD Thesis, The University of Melbourne (2024)
"Low Depth Virtual Distillation of Quantum Circuits by Deterministic Circuit Decomposition"
Akib Karim, Shaobo Zhang, Muhammad Usman
https://arxiv.org/abs/2402.18874 (2024)
"A two-stage solution to quantum process tomography: error analysis and optimal design"
Shuixin Xiao, Yuanlong Wang, Jun Zhang, Daoyi Dong, Gary J Mooney, Ian R Petersen, Hidehiro Yonezawa
https://arxiv.org/abs/2402.08952 (2024)
"Crosstalk Attacks and Defence in a Shared Quantum Computing Environment"
Benjamin Harper, Behnam Tonekaboni, Bahar Goldozian, Martin Sevior, Muhammad Usman
https://arxiv.org/abs/2402.02753 (2024)
"Permutation invariant encodings for quantum machine learning with point cloud data"
Jamie Heredge, Charles D Hill, Lloyd C L Hollenberg, Martin Sevior
Quantum Machine Intelligence (2024)
"A kernel-based quantum random forest for improved classification"
Maiyuren Srikumar, Charles D Hill, Lloyd C L Hollenberg
Quantum Machine Intelligence (2024)
"Generation and Preservation of Large Entangled States on Physical Quantum Devices"
John F Kam, Haiyue Kang, Charles D Hill, Gary J Mooney, Lloyd C L Hollenberg
https://arxiv.org/abs/2312.15170 (Dec 2023)
"Unifying non-Markovian characterisation with an efficient and self-consistent framework"
Gregory A L White, Petar Jurcevic, Charles D Hill, Kavan Modi
https://arxiv.org/abs/2312.08454 (Dec 2023)
"Kernel Alignment for Quantum Support Vector Machines Using Genetic Algorithms"
Floyd M Creevey, Jamie A Heredge, Martin E Sevior, Lloyd C L Hollenberg
https://arxiv.org/abs/2312.01562 (2023)
"Scalable Characterisation of Entanglement on Physical Quantum Computers"
Haiyue Kang
Master of Science Thesis, The University of Melbourne (2023)
"Truncated phase-based quantum arithmetic: Error propagation and resource reduction"
Gregory A L White, Charles D Hill, Lloyd C L Hollenberg
Physical Review A (2023)
"Precision ground-state energy calculation for the water molecule on a superconducting quantum processor"
Michael A Jones, Harish J Vallury, Lloyd C L Hollenberg
https://arxiv.org/abs/2311.02533 (2023)
"Filtering crosstalk from bath non-Markovianity via spacetime classical shadows"
Gregory A L White, Kavan Modi, Charles D Hill
Physical Review Letters (Apr 2023)
"Artificial Neural Network Syndrome Decoding on IBM Quantum Processors"
Brhyeton Hall, Spiro Gicev, Muhammad Usman
https://arxiv.org/abs/2311.15146 (2023)
"Quantum computer error structure probed by quantum error correction syndrome measurements"
Spiro Gicev, Lloyd C L Hollenberg, Muhammad Usman
https://arxiv.org/abs/2310.12448 (2023)
"Quantum autoencoders using mixed reference states"
Hailan Ma, Gary J Mooney, Ian R Petersen, Lloyd C L Hollenberg, Daoyi Dong
https://arxiv.org/abs/2309.15582 (2023)
"Drastic Circuit Depth Reductions with Preserved Adversarial Robustness by Approximate Encoding for Quantum Machine Learning"
Maxwell T West, Azar C Nakhl, Jamie Heredge, Floyd M Creevey, Lloyd CL Hollenberg, Martin Sevior, Muhammad Usman
https://arxiv.org/abs/2309.09424 (2023)
"Arbitrary Ground State Observables from Quantum Computed Moments"
Harish J Vallury, Lloyd C L Hollenberg
2023 IEEE International Conference on Quantum Computing and Engineering (QCE) (2023)
"Noise-robust ground state energy estimates from deep quantum circuits"
Harish J Vallury, Michael A Jones, Gregory A L White, Floyd M Creevey, Charles D Hill, Lloyd C L Hollenberg
Quantum (2023)
"Boosted Ensembles of Qubit and Continuous Variable Quantum Support Vector Machines for B Meson Flavour Tagging"
Maxwell T West, Martin Sevior, Muhammad Usman
Advanced Quantum Technologies (2023)
"Reflection Equivariant Quantum Neural Networks for Enhanced Image Classification"
Maxwell West, Martin Sevior, Muhammad Usman
Machine Learning: Science and Technology (2023)
"GASP: a genetic algorithm for state preparation on quantum computers"
Floyd M. Creevy, Charles D. Hill, Lloyd C. L. Hollenberg
Scientific Reports (2023)
"Towards quantum enhanced adversarial robustness in machine learning"
Maxwell T. West, Shu-Lok Tsang, Jia S. Low, Charles D. Hill, Christopher Leckie, Lloyd C. L. Hollenberg, Sarah M. Erfani, Muhammad Usman
Nature Machine Intelligence (2023)
"Quantum computing: a new paradigm for ecology"
Andrew P. Woolnough, Lloyd C. L. Hollenberg, Phillip Cassey, Thomas A. A. Prowse
Trends in Ecology & Evolution (2023)
"Many-time physics in practice"
Gregory A L White
PhD Thesis, The University of Melbourne (Apr 2023)
"Benchmarking adversarially robust quantum machine learning at scale"
Maxwell T. West, Sarah M. Erfani, Christopher Leckie, Martin Sevior, Lloyd C. L. Hollenberg, Muhammad Usman
Physical Review Research (2023)
"Automated Quantum Circuit Design With Nested Monte Carlo Tree Search"
Peiyong Wang, Muhammad Usman, Udaya Parampalli, Lloyd C. L. Hollenberg, Casey R. Myers
IEEE Transactions on Quantum Engineering (2023)
"A scalable and fast artificial neural network syndrome decoder for surface codes"
Spiro Gicev, Lloyd C. L. Hollenberg, Muhammad Usman
Quantum (2023)
"Large-Scale Entanglement on Physical Quantum Devices"
John Fidel Kam
Master of Science Thesis, The University of Melbourne (2022)
"Realization of a discrete time crystal on 57 qubits of a quantum computer"
Philipp Frey and Stephan Rachel
Science Advances, Vol 8, Issue 9 (2022)
Featured in The Conversation and Pursuit.
"Chemistry beyond the Hartree-Fock limit via quantum computed moments"
Michael A. Jones, Harish J. Vallury, Charles D. Hill, Lloyd C. L. Hollenberg
Scientific Reports (2022)
"From many-body to many-time physics"
Gregory A. L. White, Felix A. Pollock, Lloyd C. L. Hollenberg, Charles D. Hill, Kavan Modi
https://arxiv.org/abs/2107.13934 (2022)
"Clustering and enhanced classification using a hybrid quantum autoencoder"
Maiyuren Srikumar, Charles D. Hill, Lloyd C. L. Hollenberg
Quantum Science and Technology (2022)
"Non-Markovian Quantum Process Tomography"
Gregory A. L. White, Felix A. Pollock, Lloyd C. L. Hollenberg, Kavan Modi, Charles D. Hill
PRX Quantum (2022)
"Optimizing Quantum Logic Gates on Superconducting Transmon Qubits"
Eugene Y Huang
Master of Science Thesis, The University of Melbourne (June 2022)
"Traffic Optimization via a Hybrid Quantum Algorithm"
Jedwin Villanueva
Master of Science Thesis, The University of Melbourne (May 2022)
"Entanglement in superconducting quantum devices and improving quantum circuit compilation"
Gary J Mooney
PhD Thesis, The University of Melbourne (2022)
“Simulating the Exchange Statistics of Majorana Zero Modes on an IBM Quantum Computer”
Benjamin Harris
Master of Science Thesis, The University of Melbourne (Feb 2022)
"Process Tomography on a 7-Qubit Quantum Processor via Tensor Network Contraction Path Finding"
Aidan Dang, Gregory A. L. White, Lloyd C. L. Hollenberg, Charles D. Hill
https://arxiv.org/abs/2112.06364 (2021)
"Truncated phase-based quantum arithmetic: error propagation and resource reduction"
Gregory A L White, Charles D Hill, Lloyd C L Hollenberg
https://arxiv.org/abs/2110.00217 (2021)
"Quantum Support Vector Machines for Continuum Suppression in B Meson Decays"
Jamie Heredge, Charles Hill, Lloyd Hollenberg, Martin Sevior
Computing and Software for Big Science (2021)
"New pathways towards quantum sequence alignment with quantum neurons and quantum machine learning"
Mingrui Jing
Master of Science Thesis, The University of Melbourne (Nov 2021)
"Whole-device entanglement in a 65-qubit superconducting quantum computer"
Gary J Mooney, Gregory A L White, Charles D Hill, Lloyd C L Hollenberg
Advanced Quantum Technologies (2021)
Featured in IBM Research Blog.
"Generation and verification of 27-qubit Greenberger-Horne-Zeilinger states in a superconducting quantum computer"
Gary J Mooney, Gregory A L White, Charles D Hill, Lloyd C L Hollenberg
Journal of Physics Communications (2021)
Featured in IBM Research Blog.
"Optimising Control of Superconducting Quantum Computers Through Pulse Programming"
Timothy Kay
Master of Science Thesis, The University of Melbourne (May 2021)
"Cost optimal gate synthesis in the Clifford hierarchy"
Gary J Mooney, Charles D Hill, Lloyd C L Hollenberg
Quantum 5, 396 (2021)
"Performance optimization for drift-robust fidelity improvement of two-qubit gates"
Gregory A L White, Charles D Hill, Lloyd C L Hollenberg
Physical Review Applied (Jan 2021)
“Quantum Simulation of Spin Chains on Quantum Computers”
Zi Cheng
Master of Science Thesis, The University of Melbourne (Dec 2020)
“Demonstration of non-Markovian process characterisation and control on a quantum processor”
Gregory A L White, Felix A Pollock, Charles D Hill, Lloyd C L Hollenberg, Kavan Modi
Nature Communications, 11, 6301 (Dec 2020)
“Quantum computed moments correction to variational estimates”
Harish Vallury, Michael Jones, Charles D Hill and Lloyd C L Hollenberg
Quantum 4, 373 (2020)
“Entanglement in a 20-Qubit Superconducting Quantum Computer”
Gary J Mooney, Charles D Hill and Lloyd C L Hollenberg
Scientific Reports 9, 13465 (2019)
Quantum User Interface
The Hollenberg group has developed a sophisticated quantum computer simulation tool – the Quantum User Interface (QUI) – for use in research and teaching.
The QUI system is integrated into the following subjects:
The IBM Quantum Hub at the University of Melbourne is the only university-based Quantum Hub in Australia and New Zealand. The team has decades of combined expertise in the field of quantum computing.
Academics
| Prof Lloyd Hollenberg (Physics) – Quantum Hub Director | Dr Gary Mooney (Physics) |
| Prof Udaya Parampalli (Computer Science) | Dr Lucas Fabian Hackl (Physics, Mathematics and Statistics) |
| Dr Josh Combes (Physics, Mathematics and Statistics) | Prof Kate Smith-Miles (Mathematics and Statistics) |
| A/Prof Stephan Rachel (Physics) | Dr Usman Muhammad (Physics/CSIRO) |
| Prof Martin Sevior (Physics) | Dr Thomas Quella (Mathematics and Statistics) |
| Prof Andy Martin (Physics) | Prof Carsten Murawski (Finance) |
| Dr Nitin Yadev (Finance) | Dr Eric Mascot (Physics) |
| Dr Philipp Frey (Physics) | Dr Marion Umbach (Physics) |
| Prof Rajkumar Buyya (Computer Science) | A/Prof Sarah Monazam Erfani (Computer Science) |
| Prof Chris Leckie (Computer Science) | Prof Adrian Pearce (Computer Science) |
Collaborators
| Centre of Excellence for Quantum Biotechnology (QUBIC) |
| A/Prof Kavan Modi (Physics, Monash University) |
| Prof Daoyi Dong (Engineering, Australian National University) |
Student Researchers
| Floyd Creevey (PhD, Physics) | Michael Jones (PhD, Physics) |
| Harish Vallury (PhD, Physics) | Chris Nakhl (PhD, Physics) |
| Ben Harper (PhD, Physics) | Spiro Gicev (PhD, Physics) |
| Haiyue Kang (PhD, Physics) | Maxwell West (PhD, Physics) |
| Sarama Tonetto (PhD, Physics) | Shaobo Zhang (PhD, Computer Science) |
| Maiyuren Srikumar (PhD, Physics) | Younghun Kim (PhD, Physics) |
| Peiyong Wang (PhD, Computer Science) | Hoa Nguyen (PhD, Computer Science) |
| Vivek Katial (PhD, Mathematics and Statistics) | Kanwal Aslam Syed (PhD, Computer Science) |
| Zhenzhi Lai (PhD, Computer Science) | Hevish Cowlessur (PhD, Computer Science) |
| Bacui Li (PhD, Computer Science) | Alana Fiusco (MSc, Physics) |
| Jedwin Villaneuva (MSc, Physics) | James Nelson (MSc, Mathematics and Statistics) |
| Con Kavadias (MCS, Computer Science) | Henry Jackson (MIT, Computer Science) |
| Leting Zhouli (MIT, Computer Science) |